Kathryn H. Brown
- Pulmonary and Respiratory Medicine top 1%
- Oncology top 2%
- Molecular Biology top 10%
- Cancer Research top 5%
- Organic Chemistry top 10%
- Co-authors
- Mireille CantariniEnriqueta FelipDavid PlanchardPasi A. JänneMalcolm RansonYuichiro OhePaul A. DickinsonSuresh S. Ramalingam
- Topics
- Radiomics and Machine Learning in Medical Imaging (5 papers)Advanced X-ray and CT Imaging (5 papers)PI3K/AKT/mTOR signaling in cancer (4 papers)
- Partner nations
- United KingdomUnited StatesNetherlands
In The Last Decade
Kathryn H. Brown
28 papers receiving 2.4k citations
Hit Papers
Peers
Comparison fields: 5 of 84
- Pulmonary and Respiratory Medicine 1.8k
- Oncology 1.4k
- Molecular Biology 931
- Cancer Research 460
- Organic Chemistry 169
Countries citing papers authored by Kathryn H. Brown
This map shows the geographic impact of Kathryn H. Brown's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Kathryn H. Brown with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kathryn H. Brown more than expected).
Fields of papers citing papers by Kathryn H. Brown
This network shows the impact of papers produced by Kathryn H. Brown. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Kathryn H. Brown. The network helps show where Kathryn H. Brown may publish in the future.
Co-authorship network of co-authors of Kathryn H. Brown
This figure shows the co-authorship network connecting the top 25 collaborators of Kathryn H. Brown. A scholar is included among the top collaborators of Kathryn H. Brown based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kathryn H. Brown. Kathryn H. Brown is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 6 | |
| 5 | 4 | |
| 6 | 5 | |
| 7 | 18 | |
| 8 | 9 | |
| 9 | 115 | |
| 10 | AZD9291 in EGFR Inhibitor–Resistant Non–Small-Cell Lung Cancerbreakdown → | 1585 |
| 11 | 33 | |
| 12 | 5 | |
| 13 | 7 | |
| 14 | 23 | |
| 15 | 16 | |
| 16 | 176 | |
| 17 | 27 | |
| 18 | 16 | |
| 19 | 3 | |
| 20 | Growth, physique and age at menarche of Mexican American females aged 12 through 17 years residing in San Diego County, California | 5 |
About Kathryn H. Brown
Kathryn H. Brown is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Hematology, having authored 30 papers that have together received 2.4k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (5 papers), Advanced X-ray and CT Imaging (5 papers) and PI3K/AKT/mTOR signaling in cancer (4 papers). The work is most often cited by research in Pulmonary and Respiratory Medicine (1.8k citations), Oncology (1.4k citations) and Cancer Research (460 citations). Kathryn H. Brown has collaborated with scholars based in United Kingdom, United States and Netherlands. Frequent co-authors include Mireille Cantarini, Enriqueta Felip, David Planchard, Pasi A. Jänne, Malcolm Ranson, Yuichiro Ohe, Paul A. Dickinson, Suresh S. Ramalingam, Wu‐Chou Su and James Chih‐Hsin Yang. Their work appears in journals such as New England Journal of Medicine, Journal of Clinical Oncology and Blood.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.